Automated detection of damage due to impact in composite structures is very important for aerospace structural health
monitoring (SHM) applications. Fiber Bragg grating (FBG) sensors show promise in aerospace applications since they
are immune to electromagnetic interference and can support multiple sensors in a single fiber. However, since they only
measure strain along the length of the fiber, a prediction scheme that can estimate loading using randomly oriented
sensors is key to damage state awareness. This paper focuses on the prediction of impact loading in composite structures
as a function of time using a support vector regression (SVR) approach. A time delay embedding feature extraction
scheme is used since it can characterize the dynamics of the impact using the sensor signal from the FBGs. The
efficiency of this approach has been demonstrated on simulated composite plates and wing structures. Training with
impacts at four locations with three different energies, the constructed framework is able to predict the force-time history
at an unknown impact location to within 12 percent on the composite plate and to within 10 percent on a composite wing when the impact was within the sensor network region.

Localization of low energy impacts on carbon fiber composites is an important aspect of structural health monitoring
since it creates subsurface damage which can significantly reduce the stiffness of a component. A novel impact
localization method is proposed based on the strain amplitude measured by Fiber Bragg Grating (FBG) sensors. The
algorithm is based on the relative placement of all sensors and the maximum strain amplitude measured by each sensor.
This method requires minimal knowledge of the material or the structure and a minimum number of sensors. The
algorithm showed good results on both simulated and experimental test cases of woven composite plates. It was found
that a minimum of five FBG are necessary to accurately predict the impact location on a plate. The algorithm was also
tested on a woven composite wing showing good localization along the span of the wing but higher errors along the chord length due to the nonlinearity in the measured strains.

Woven fiber composites are currently being investigated due to their advantages over other materials, making them
suitable for low weight, high stiffness, and high interlaminar fracture toughness applications such as missiles, body
armor, satellites, and many other aerospace applications. Damage characterization of woven fabrics is a complex task
due to their tendency to exhibit different failure modes based on the weave configuration, orientation, ply stacking and
other variables. A multiscale model is necessary to accurately predict progressive damage. The present research is an
experimental study on damage characterization of three different woven fiber laminates under low energy impact using
Fiber Bragg Grating (FBG) sensors and flash thermography. A correlation between the measured strain from FBG
sensors and the damaged area obtained from flash thermography imaging has been developed. It was observed that the
peak strain in the fabrics were strongly dependent on the weave geometry and decreased at different rates as damage area
increased due to dissimilar failure modes. Experimental observations were validated with the development of a
multiscale model. A FBG sensor placement model was developed which showed that FBG sensor location and
orientation plays a key role in the sensing capabilities of strain on the samples.

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